Google Gemini

1. 概述

Google 推出的多模态人工智能模型，旨在处理多种数据类型，包括文本、图像、音频、视频和代码。

本 API 与 OpenAI 接口格式兼容。

模型列表：

gemini-1.5-pro
gemini-1.5-pro-001
gemini-1.5-pro-002
gemini-1.5-flash-001
gemini-1.5-flash-002
gemini-1.5-flash-8b
gemini-1.5-pro-latest
gemini-2.0-flash
gemini-2.0-flash-lite-preview-02-05
gemini-2.5-flash-preview-04-17 (2025/07/15停用)
gemini-2.5-flash-preview-05-20 (2025/07/15停用)
gemini-2.5-flash
gemini-2.5-pro-preview-05-06 (2025/07/15停用)
gemini-2.5-pro-preview-06-05 (2025/07/15停用)
gemini-2.5-pro
gemini-2.5-flash-lite-preview-06-17
gemini-2.5-flash-thinking (输出思考过程)
gemini-2.5-pro-thinking (输出思考过程)

模型名称里包含exp的为实验性模型，不太稳定，建议只用来进行实验性测试。

2. 请求说明

请求方法:POST
请求地址:
https://gateway.theturbo.ai/v1/chat/completions

3. 请求参数

3.1 Header 参数

参数名称

类型

必填

说明

示例值

Content-Type

string

是

设置请求头类型，必须为 application/json

application/json

Accept

string

是

设置响应类型，建议统一为 application/json

application/json

Authorization

string

是

身份验证所需的 API_KEY，格式 Bearer $YOUR_API_KEY

Bearer $YOUR_API_KEY

3.2 Body 参数 (application/json)

参数名称

类型

必填

说明

示例

model

string

是

要使用的模型 ID。详见概述列出的可用版本，如 gemini-1.5-pro。

gemini-1.5-pro

messages

array

是

聊天消息列表，格式与 OpenAI 兼容。数组中的每个对象包含 role(角色) 与 content(内容)。

[{"role": "user","content": "你好"}]

role

string

否

消息角色，可选值：system、user、assistant。

user

content

string/array

否

消息的具体内容。

你好，请给我讲个笑话。

temperature

number

否

采样温度，取值 0～2。数值越大，输出越随机；数值越小，输出越集中和确定。

0.7

top_p

number

否

另一种调节采样分布的方式，取值 0～1。和 temperature 通常二选一设置。

0.9

number

否

为每条输入消息生成多少条回复。

1

stream

boolean

否

是否开启流式输出。设置为 true 时，返回类似 ChatGPT 的流式数据。

false

stop

string

否

最多可指定 4 个字符串，一旦生成的内容出现这几个字符串之一，就停止生成更多 tokens。

"\n"

max_tokens

number

否

单次回复可生成的最大 token 数量，受模型上下文长度限制。

1024

presence_penalty

number

否

-2.0 ~ 2.0。正值会鼓励模型输出更多新话题，负值会降低输出新话题的概率。

0

frequency_penalty

number

否

-2.0 ~ 2.0。正值会降低模型重复字句的频率，负值会提高重复字句出现的概率。

0

reasoning_effort

string

否

用来控制模型在推理任务中投入多少“计算精力”。目前只有gemini-2.5-flash-preview-04-17支持。支持low medium high none。默认为low。

low

web_search_options

object

否

用来控制是否开启google搜索提示依据。

{}

4. 请求示例

4.1 聊天对话

POST /v1/chat/completions
Content-Type: application/json
Accept: application/json
Authorization: Bearer $YOUR_API_KEY

{
	"model": "gemini-1.5-pro",
	"messages": [
		{
			"role": "user",
			"content": "你好，给我科普一下量子力学吧"
		}
	],
	"temperature": 0.7,
	"max_tokens": 1024
}

curl https://gateway.theturbo.ai/v1/chat/completions \
	-H "Content-Type: application/json" \
	-H "Accept: application/json" \
	-H "Authorization: Bearer $YOUR_API_KEY" \
	-d "{
	\"model\": \"gemini-1.5-pro\",
	\"messages\": [{
		\"role\": \"user\",
		\"content\": \"你好，给我科普一下量子力学吧\"
	}]
}"

package main

import (
	"fmt"
	"io/ioutil"
	"net/http"
	"strings"
)

const (
	YOUR_API_KEY    = "sk-123456789012345678901234567890123456789012345678"
	REQUEST_PAYLOAD = `{
	"model": "gemini-1.5-pro",
	"messages": [{
		"role": "user",
		"content": "你好，给我科普一下量子力学吧"
	}],
	"temperature": 0.7,
	"max_tokens": 1024
}`
)

func main() {

	requestURL := "https://gateway.theturbo.ai/v1/chat/completions"
	requestMethod := "POST"
	requestPayload := strings.NewReader(REQUEST_PAYLOAD)

	req, err := http.NewRequest(requestMethod, requestURL, requestPayload)
	if err != nil {
		fmt.Println("Create request failed, err: ", err)
		return
	}

	req.Header.Add("Content-Type", "application/json")
	req.Header.Add("Accept", "application/json")
	req.Header.Add("Authorization", "Bearer "+YOUR_API_KEY)

	client := &http.Client{}

	resp, err := client.Do(req)
	if err != nil {
		fmt.Println("Do request failed, err: ", err)
		return
	}
	defer resp.Body.Close()

	respBodyBytes, err := ioutil.ReadAll(resp.Body)
	if err != nil {
		fmt.Println("Read response body failed, err: ", err)
		return
	}
	fmt.Println(string(respBodyBytes))
}

4.2 媒体文件理解

媒体文件理解功能，支持理解文档、图像、音频、视频，详细支持类型请参照下方“支持的媒体类型”。

POST /v1/chat/completions
Content-Type: application/json
Accept: application/json
Authorization: Bearer $YOUR_API_KEY

{
	"model": "gemini-1.5-pro",
	"messages": [
		{
			"role": "user",
			"content": [
				{
					"type": "text",
					"text": "这张图片里有什么？"
				},
				{
					"type": "image_url",
					"image_url": {
						"url": "data:image/jpeg;base64,${base64_image}"
					}
				}
			]
		}
	],
	"temperature": 0.7,
	"max_tokens": 1024
}

base64_image=$(base64 -i "Path/to/agi/image.jpeg");
curl https://gateway.theturbo.ai/v1/chat/completions \
	-H "Content-Type: application/json" \
	-H "Accept: application/json" \
	-H "Authorization: Bearer $YOUR_API_KEY" \
	-d "{
	\"model\": \"gemini-1.5-pro\",
	\"messages\": [{
		\"role\": \"user\",
		\"content\": [{
				\"type\": \"text\",
				\"text\": \"这张图片里有什么？\"
			},
			{
				\"type\": \"image_url\",
				\"image_url\": {
					\"url\": \"data:image/jpeg;base64,${base64_image}\"
				}
			}
		]
	}]
}"

package main

import (
	"encoding/base64"
	"fmt"
	"io/ioutil"
	"net/http"
	"os"
	"strings"
)

const (
	YOUR_API_KEY    = "sk-123456789012345678901234567890123456789012345678"
	FILE_MIME_TYPE  = "image/jpeg"
	FILE_PATH       = "/path/to/your/image.jpeg"
	REQUEST_PAYLOAD = `{
	"model": "gemini-1.5-pro",
	"messages": [{
		"role": "user",
		"content": [{
				"type": "text",
				"text": "这张图片里有什么？"
			},
			{
				"type": "image_url",
				"image_url": {
					"url": "data:%s;base64,%s"
				}
			}
		]
	}],
	"temperature": 0.7,
	"max_tokens": 1024
}`
)

func GetFileDataBase64(filePath string) (string, error) {

	file, err := os.Open(FILE_PATH)
	if err != nil {
		return "", err
	}
	defer file.Close()

	fileData, err := ioutil.ReadAll(file)
	if err != nil {
		return "", err
	}

	return base64.StdEncoding.EncodeToString(fileData), nil
}

func main() {

	requestURL := "https://gateway.theturbo.ai/v1/chat/completions"
	requestMethod := "POST"

	fileBase64String, err := GetFileDataBase64(FILE_PATH)
	if err != nil {
		fmt.Println("Read file failed, err: ", err)
		return
	}

	requestPayload := strings.NewReader(fmt.Sprintf(REQUEST_PAYLOAD,
		FILE_MIME_TYPE,
		fileBase64String,
	))

	req, err := http.NewRequest(requestMethod, requestURL, requestPayload)
	if err != nil {
		fmt.Println("Create request failed, err: ", err)
		return
	}

	req.Header.Add("Content-Type", "application/json")
	req.Header.Add("Accept", "application/json")
	req.Header.Add("Authorization", "Bearer "+YOUR_API_KEY)

	client := &http.Client{}

	resp, err := client.Do(req)
	if err != nil {
		fmt.Println("Do request failed, err: ", err)
		return
	}
	defer resp.Body.Close()

	respBodyBytes, err := ioutil.ReadAll(resp.Body)
	if err != nil {
		fmt.Println("Read response body failed, err: ", err)
		return
	}
	fmt.Println(string(respBodyBytes))
}

支持的媒体类型

图片类型：

image/png image/jpeg image/webp image/heic image/heif

音频类型：

audio/wav audio/mp3 audio/aiff audio/aac audio/ogg audio/flac

视频类型：

video/mp4 video/mpeg video/mov video/avi video/x-flv video/mpg video/webm video/wmv video/3gpp

文档类型：

application/pdf application/x-javascript text/javascript application/x-python text/x-python text/plain text/html text/css text/md text/csv text/xml text/rtf

本 API 兼容 OpenAI 接口格式，采用 OpenAI 的image_url 字段支持所有媒体类型。

本 API 提交媒体文件只支持以base64的形式上传，不支持http地址。

4.3 函数调用

POST /v1/chat/completions
Content-Type: application/json
Accept: application/json
Authorization: Bearer $YOUR_API_KEY

{
	"model": "gemini-1.5-pro",
	"messages": [{
		"role": "user",
		"content": "What's the weather like in Boston today?"
	}],
	"tools": [{
		"type": "function",
		"function": {
			"name": "get_current_weather",
			"description": "Get the current weather in a given location",
			"parameters": {
				"type": "object",
				"properties": {
					"location": {
						"type": "string",
						"description": "The city and state, e.g. San Francisco, CA"
					},
					"unit": {
						"type": "string",
						"enum": ["celsius", "fahrenheit"]
					}
				},
				"required": ["location"]
			}
		}
	}],
	"tool_choice": "auto"
}

curl https://gateway.theturbo.ai/v1/chat/completions \
	-H "Content-Type: application/json" \
	-H "Accept: application/json" \
	-H "Authorization: Bearer $YOUR_API_KEY" \
	-d "{
	\"model\": \"gemini-1.5-pro\",
	\"messages\": [{
		\"role\": \"user\",
		\"content\": \"What's the weather like in Boston today?\"
	}],
	\"tools\": [{
		\"type\": \"function\",
		\"function\": {
			\"name\": \"get_current_weather\",
			\"description\": \"Get the current weather in a given location\",
			\"parameters\": {
				\"type\": \"object\",
				\"properties\": {
					\"location\": {
						\"type\": \"string\",
						\"description\": \"The city and state, e.g. San Francisco, CA\"
					},
					\"unit\": {
						\"type\": \"string\",
						\"enum\": [\"celsius\", \"fahrenheit\"]
					}
				},
				\"required\": [\"location\"]
			}
		}
	}],
	\"tool_choice\": \"auto\"
}"

package main

import (
	"fmt"
	"io/ioutil"
	"net/http"
	"strings"
)

const (
	YOUR_API_KEY    = "sk-123456789012345678901234567890123456789012345678"
	REQUEST_PAYLOAD = `{
	"model": "gemini-1.5-pro",
	"messages": [{
		"role": "user",
		"content": "What's the weather like in Boston today?"
	}],
	"tools": [{
		"type": "function",
		"function": {
			"name": "get_current_weather",
			"description": "Get the current weather in a given location",
			"parameters": {
				"type": "object",
				"properties": {
					"location": {
						"type": "string",
						"description": "The city and state, e.g. San Francisco, CA"
					},
					"unit": {
						"type": "string",
						"enum": ["celsius", "fahrenheit"]
					}
				},
				"required": ["location"]
			}
		}
	}],
	"tool_choice": "auto"
}`
)

func main() {

	requestURL := "https://gateway.theturbo.ai/v1/chat/completions"
	requestMethod := "POST"
	requestPayload := strings.NewReader(REQUEST_PAYLOAD)

	req, err := http.NewRequest(requestMethod, requestURL, requestPayload)
	if err != nil {
		fmt.Println("Create request failed, err: ", err)
		return
	}

	req.Header.Add("Content-Type", "application/json")
	req.Header.Add("Accept", "application/json")
	req.Header.Add("Authorization", "Bearer "+YOUR_API_KEY)

	client := &http.Client{}

	resp, err := client.Do(req)
	if err != nil {
		fmt.Println("Do request failed, err: ", err)
		return
	}
	defer resp.Body.Close()

	respBodyBytes, err := ioutil.ReadAll(resp.Body)
	if err != nil {
		fmt.Println("Read response body failed, err: ", err)
		return
	}
	fmt.Println(string(respBodyBytes))
}

4.4 Google Search

将 Gemini 模型与实时网络内容相关联，并且适用于所有可用语言。这样一来，Gemini 就可以提供更准确的回答，并引用其知识断点之外的可验证来源。

目前只有gemini-2.5-pro与gemini-2.5-flash系列模型支持该功能

POST /v1/chat/completions
Content-Type: application/json
Accept: application/json
Authorization: Bearer $YOUR_API_KEY

{
	"model": "gemini-2.5-pro",
	"messages": [
		{
			"role": "user",
			"content": "你好，波士顿最近天气怎么样"
		}
	],
	"temperature": 0.7,
	"max_tokens": 1024,
	"web_search_options": {}
}

curl https://gateway.theturbo.ai/v1/chat/completions \
	-H "Content-Type: application/json" \
	-H "Accept: application/json" \
	-H "Authorization: Bearer $YOUR_API_KEY" \
	-d "{
	\"model\": \"gemini-2.5-pro\",
	\"messages\": [{
		\"role\": \"user\",
		\"content\": \"你好，波士顿最近天气怎么样\"
	}],
	\"temperature\": 0.7,
	\"max_tokens\": 1024,
	\"web_search_options\": {}
}"

package main

import (
	"fmt"
	"io/ioutil"
	"net/http"
	"strings"
)

const (
	YOUR_API_KEY    = "sk-123456789012345678901234567890123456789012345678"
	REQUEST_PAYLOAD = `{
	"model": "gemini-2.5-pro",
	"messages": [{
		"role": "user",
		"content": "你好，波士顿最近天气怎么样"
	}],
	"temperature": 0.7,
	"max_tokens": 1024,
	"web_search_options": {}
}`
)

func main() {

	requestURL := "https://gateway.theturbo.ai/v1/chat/completions"
	requestMethod := "POST"
	requestPayload := strings.NewReader(REQUEST_PAYLOAD)

	req, err := http.NewRequest(requestMethod, requestURL, requestPayload)
	if err != nil {
		fmt.Println("Create request failed, err: ", err)
		return
	}

	req.Header.Add("Content-Type", "application/json")
	req.Header.Add("Accept", "application/json")
	req.Header.Add("Authorization", "Bearer "+YOUR_API_KEY)

	client := &http.Client{}

	resp, err := client.Do(req)
	if err != nil {
		fmt.Println("Do request failed, err: ", err)
		return
	}
	defer resp.Body.Close()

	respBodyBytes, err := ioutil.ReadAll(resp.Body)
	if err != nil {
		fmt.Println("Read response body failed, err: ", err)
		return
	}
	fmt.Println(string(respBodyBytes))
}

5. 响应示例

{
	"id": "chatcmpl-1234567890",
	"object": "chat.completion",
	"created": 1699999999,
	"model": "gemini-1.5-pro",
	"choices": [
		{
			"message": {
				"role": "assistant",
				"content": "量子力学是研究微观世界的物理学分支……"
			},
			"finish_reason": "stop"
		}
	],
	"usage": {
		"prompt_tokens": 10,
		"completion_tokens": 30,
		"total_tokens": 40
	}
}

最后更新于3个月前